Testing the ability of trajectory statistics to reproduce emission inventories of air pollutants in cases of negligible measurement and transport errors

Methods of trajectory statistics have often been used in combination with air quality measurements to identify source areas of air pollutants. Due to many limitations, it is not clear which share of the deviations between results of the statistics and (independent) emission inventories could really be attributed to the methods applied, and which share is due to problems with the input data, for example wrong measurements and erroneous air trajectories. In this study, we tested two well-known statistical methods under conditions of negligible measurement and transport errors by applying them to concentrations of total reactive nitrogen computed by a Lagrangian box model using exactly the same trajectories as input. The resulting concentration fields of total reactive nitrogen were compared to the emission inventory of nitric oxides used by the model. Two test data sets were constructed, namely one “ideal” set neglecting temporal variations of emissions and deposition, and one “real” set considering these processes. As a result, it was shown that both methods were in principle successful in reproducing the most important features of the emission inventory. It can be concluded that such statistical methods, with some limitations, are helpful in investigating source–receptor relationships of air pollutants, provided that the measurements are accurate and representative and that the trajectories reasonably well describe pollutant transport.